Overview

Dataset statistics

Number of variables56
Number of observations15120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 MiB
Average record size in memory448.0 B

Variable types

BOOL44
NUM12

Warnings

Soil_Type7 has constant value "15120" Constant
Soil_Type15 has constant value "15120" Constant
Id has unique values Unique
Horizontal_Distance_To_Hydrology has 1590 (10.5%) zeros Zeros
Vertical_Distance_To_Hydrology has 1890 (12.5%) zeros Zeros

Reproduction

Analysis started2020-12-22 16:51:11.292861
Analysis finished2020-12-22 16:52:00.541909
Duration49.25 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Id
Real number (ℝ≥0)

UNIQUE

Distinct15120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7560.5
Minimum1
Maximum15120
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2020-12-22T11:52:00.678789image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile756.95
Q13780.75
median7560.5
Q311340.25
95-th percentile14364.05
Maximum15120
Range15119
Interquartile range (IQR)7559.5

Descriptive statistics

Standard deviation4364.91237
Coefficient of variation (CV)0.5773311779
Kurtosis-1.2
Mean7560.5
Median Absolute Deviation (MAD)3780
Skewness0
Sum114314760
Variance19052460
MonotocityStrictly increasing
2020-12-22T11:52:00.848792image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
67581< 0.1%
 
149781< 0.1%
 
88331< 0.1%
 
108801< 0.1%
 
47271< 0.1%
 
67741< 0.1%
 
6291< 0.1%
 
26761< 0.1%
 
129151< 0.1%
 
149621< 0.1%
 
88171< 0.1%
 
108641< 0.1%
 
47111< 0.1%
 
6131< 0.1%
 
26921< 0.1%
 
26601< 0.1%
 
128991< 0.1%
 
149461< 0.1%
 
88011< 0.1%
 
108481< 0.1%
 
46951< 0.1%
 
67421< 0.1%
 
5971< 0.1%
 
26441< 0.1%
 
Other values (15095)1509599.8%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
61< 0.1%
 
71< 0.1%
 
81< 0.1%
 
91< 0.1%
 
101< 0.1%
 
ValueCountFrequency (%) 
151201< 0.1%
 
151191< 0.1%
 
151181< 0.1%
 
151171< 0.1%
 
151161< 0.1%
 
151151< 0.1%
 
151141< 0.1%
 
151131< 0.1%
 
151121< 0.1%
 
151111< 0.1%
 

Elevation
Real number (ℝ≥0)

Distinct1665
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.322553
Minimum1863
Maximum3849
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2020-12-22T11:52:01.047789image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1863
5-th percentile2117
Q12376
median2752
Q33104
95-th percentile3397
Maximum3849
Range1986
Interquartile range (IQR)728

Descriptive statistics

Standard deviation417.6781873
Coefficient of variation (CV)0.151920402
Kurtosis-1.082115791
Mean2749.322553
Median Absolute Deviation (MAD)367
Skewness0.07563970694
Sum41569757
Variance174455.0682
MonotocityNot monotonic
2020-12-22T11:52:01.212790image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2290250.2%
 
2830250.2%
 
3371240.2%
 
3244230.2%
 
2820230.2%
 
2955230.2%
 
2795230.2%
 
2952230.2%
 
2962220.1%
 
2304220.1%
 
2809220.1%
 
2978220.1%
 
2413220.1%
 
2707220.1%
 
2850220.1%
 
2763220.1%
 
2289210.1%
 
2739210.1%
 
2827210.1%
 
2784210.1%
 
2807210.1%
 
2328210.1%
 
2311200.1%
 
3256200.1%
 
2751200.1%
 
Other values (1640)1456996.4%
 
ValueCountFrequency (%) 
18631< 0.1%
 
18741< 0.1%
 
18791< 0.1%
 
18881< 0.1%
 
18892< 0.1%
 
18961< 0.1%
 
18981< 0.1%
 
18991< 0.1%
 
19011< 0.1%
 
19032< 0.1%
 
ValueCountFrequency (%) 
38492< 0.1%
 
38481< 0.1%
 
38462< 0.1%
 
38441< 0.1%
 
38421< 0.1%
 
38391< 0.1%
 
38361< 0.1%
 
38311< 0.1%
 
38271< 0.1%
 
38252< 0.1%
 

Aspect
Real number (ℝ≥0)

Distinct361
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.6766534
Minimum0
Maximum360
Zeros110
Zeros (%)0.7%
Memory size118.2 KiB
2020-12-22T11:52:01.399777image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q165
median126
Q3261
95-th percentile344
Maximum360
Range360
Interquartile range (IQR)196

Descriptive statistics

Standard deviation110.0858014
Coefficient of variation (CV)0.7026305386
Kurtosis-1.150244484
Mean156.6766534
Median Absolute Deviation (MAD)77
Skewness0.450935294
Sum2368951
Variance12118.88367
MonotocityNot monotonic
2020-12-22T11:52:01.569763image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
451170.8%
 
01100.7%
 
901090.7%
 
63890.6%
 
76870.6%
 
27820.5%
 
315810.5%
 
75800.5%
 
108790.5%
 
117780.5%
 
34770.5%
 
72770.5%
 
121770.5%
 
135750.5%
 
80750.5%
 
57750.5%
 
53740.5%
 
62730.5%
 
124710.5%
 
86710.5%
 
61710.5%
 
111700.5%
 
18700.5%
 
84700.5%
 
52690.5%
 
Other values (336)1311386.7%
 
ValueCountFrequency (%) 
01100.7%
 
1480.3%
 
2500.3%
 
3540.4%
 
4510.3%
 
5460.3%
 
6570.4%
 
7480.3%
 
8560.4%
 
9510.3%
 
ValueCountFrequency (%) 
3602< 0.1%
 
359330.2%
 
358470.3%
 
357580.4%
 
356500.3%
 
355450.3%
 
354510.3%
 
353550.4%
 
352600.4%
 
351550.4%
 

Slope
Real number (ℝ≥0)

Distinct52
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5015873
Minimum0
Maximum52
Zeros5
Zeros (%)< 0.1%
Memory size118.2 KiB
2020-12-22T11:52:01.748787image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q110
median15
Q322
95-th percentile32
Maximum52
Range52
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.453926762
Coefficient of variation (CV)0.5123099134
Kurtosis-0.2383101358
Mean16.5015873
Median Absolute Deviation (MAD)6
Skewness0.5236583383
Sum249504
Variance71.4688777
MonotocityNot monotonic
2020-12-22T11:52:01.930214image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
117404.9%
 
107394.9%
 
137174.7%
 
146994.6%
 
126774.5%
 
96644.4%
 
156644.4%
 
166404.2%
 
175984.0%
 
85743.8%
 
75733.8%
 
185583.7%
 
205523.7%
 
195193.4%
 
214653.1%
 
64653.1%
 
224583.0%
 
234503.0%
 
54232.8%
 
243942.6%
 
253592.4%
 
263292.2%
 
283132.1%
 
43052.0%
 
272972.0%
 
Other values (27)194812.9%
 
ValueCountFrequency (%) 
05< 0.1%
 
1780.5%
 
21340.9%
 
32101.4%
 
43052.0%
 
54232.8%
 
64653.1%
 
75733.8%
 
85743.8%
 
96644.4%
 
ValueCountFrequency (%) 
521< 0.1%
 
501< 0.1%
 
495< 0.1%
 
481< 0.1%
 
473< 0.1%
 
46150.1%
 
453< 0.1%
 
445< 0.1%
 
432< 0.1%
 
423< 0.1%
 

Horizontal_Distance_To_Hydrology
Real number (ℝ≥0)

ZEROS

Distinct400
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.1957011
Minimum0
Maximum1343
Zeros1590
Zeros (%)10.5%
Memory size118.2 KiB
2020-12-22T11:52:02.105187image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q167
median180
Q3330
95-th percentile631
Maximum1343
Range1343
Interquartile range (IQR)263

Descriptive statistics

Standard deviation210.0752957
Coefficient of variation (CV)0.9246446774
Kurtosis2.803984388
Mean227.1957011
Median Absolute Deviation (MAD)120
Skewness1.488052491
Sum3435199
Variance44131.62986
MonotocityNot monotonic
2020-12-22T11:52:02.365330image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0159010.5%
 
3012078.0%
 
1504973.3%
 
604903.2%
 
424523.0%
 
674112.7%
 
853812.5%
 
1083612.4%
 
902841.9%
 
1202831.9%
 
952591.7%
 
1342551.7%
 
1242471.6%
 
2122121.4%
 
2771881.2%
 
2421881.2%
 
1621881.2%
 
1901851.2%
 
1751831.2%
 
1801741.2%
 
2011671.1%
 
1271661.1%
 
2101601.1%
 
1921601.1%
 
2281571.0%
 
Other values (375)627541.5%
 
ValueCountFrequency (%) 
0159010.5%
 
3012078.0%
 
424523.0%
 
604903.2%
 
674112.7%
 
853812.5%
 
902841.9%
 
952591.7%
 
1083612.4%
 
1202831.9%
 
ValueCountFrequency (%) 
13431< 0.1%
 
13181< 0.1%
 
12941< 0.1%
 
12612< 0.1%
 
12602< 0.1%
 
12181< 0.1%
 
12131< 0.1%
 
12081< 0.1%
 
12031< 0.1%
 
12011< 0.1%
 

Vertical_Distance_To_Hydrology
Real number (ℝ)

ZEROS

Distinct423
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.07652116
Minimum-146
Maximum554
Zeros1890
Zeros (%)12.5%
Memory size118.2 KiB
2020-12-22T11:52:02.577325image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-146
5-th percentile-4
Q15
median32
Q379
95-th percentile176
Maximum554
Range700
Interquartile range (IQR)74

Descriptive statistics

Standard deviation61.23940613
Coefficient of variation (CV)1.198973711
Kurtosis3.403498704
Mean51.07652116
Median Absolute Deviation (MAD)32
Skewness1.53777568
Sum772277
Variance3750.264863
MonotocityNot monotonic
2020-12-22T11:52:02.741325image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0189012.5%
 
52171.4%
 
32061.4%
 
42001.3%
 
81981.3%
 
71821.2%
 
101761.2%
 
91661.1%
 
21651.1%
 
61621.1%
 
111591.1%
 
121591.1%
 
131581.0%
 
221400.9%
 
141400.9%
 
11390.9%
 
201350.9%
 
231330.9%
 
161320.9%
 
171260.8%
 
191260.8%
 
211250.8%
 
-11230.8%
 
251220.8%
 
181210.8%
 
Other values (398)952063.0%
 
ValueCountFrequency (%) 
-1461< 0.1%
 
-1341< 0.1%
 
-1231< 0.1%
 
-1151< 0.1%
 
-1141< 0.1%
 
-1101< 0.1%
 
-1081< 0.1%
 
-1041< 0.1%
 
-1031< 0.1%
 
-1002< 0.1%
 
ValueCountFrequency (%) 
5541< 0.1%
 
5472< 0.1%
 
4111< 0.1%
 
4031< 0.1%
 
4011< 0.1%
 
3972< 0.1%
 
3951< 0.1%
 
3931< 0.1%
 
3901< 0.1%
 
3871< 0.1%
 

Horizontal_Distance_To_Roadways
Real number (ℝ≥0)

Distinct3250
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1714.023214
Minimum0
Maximum6890
Zeros3
Zeros (%)< 0.1%
Memory size118.2 KiB
2020-12-22T11:52:02.961325image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile242
Q1764
median1316
Q32270
95-th percentile4635.1
Maximum6890
Range6890
Interquartile range (IQR)1506

Descriptive statistics

Standard deviation1325.066358
Coefficient of variation (CV)0.7730737525
Kurtosis1.022419366
Mean1714.023214
Median Absolute Deviation (MAD)690
Skewness1.247810678
Sum25916031
Variance1755800.854
MonotocityNot monotonic
2020-12-22T11:52:03.155335image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
150880.6%
 
120560.4%
 
390470.3%
 
618450.3%
 
1110430.3%
 
700410.3%
 
108380.3%
 
1273370.2%
 
900370.2%
 
212370.2%
 
335370.2%
 
990370.2%
 
242360.2%
 
607360.2%
 
361350.2%
 
1082350.2%
 
228340.2%
 
750340.2%
 
277340.2%
 
450340.2%
 
1050340.2%
 
1020340.2%
 
960330.2%
 
1167330.2%
 
1140330.2%
 
Other values (3225)1413293.5%
 
ValueCountFrequency (%) 
03< 0.1%
 
30150.1%
 
425< 0.1%
 
60110.1%
 
67130.1%
 
85100.1%
 
90230.2%
 
95190.1%
 
108380.3%
 
120560.4%
 
ValueCountFrequency (%) 
68901< 0.1%
 
68361< 0.1%
 
68111< 0.1%
 
67661< 0.1%
 
66791< 0.1%
 
66601< 0.1%
 
65082< 0.1%
 
64141< 0.1%
 
64061< 0.1%
 
63711< 0.1%
 

Hillshade_9am
Real number (ℝ≥0)

Distinct176
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212.7042989
Minimum0
Maximum254
Zeros1
Zeros (%)< 0.1%
Memory size118.2 KiB
2020-12-22T11:52:03.363592image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile151
Q1196
median220
Q3235
95-th percentile250
Maximum254
Range254
Interquartile range (IQR)39

Descriptive statistics

Standard deviation30.56128689
Coefficient of variation (CV)0.143679686
Kurtosis1.218810484
Mean212.7042989
Median Absolute Deviation (MAD)18
Skewness-1.093680561
Sum3216089
Variance933.9922561
MonotocityNot monotonic
2020-12-22T11:52:03.583729image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2262791.8%
 
2292691.8%
 
2242651.8%
 
2282611.7%
 
2302601.7%
 
2332481.6%
 
2232451.6%
 
2192421.6%
 
2312391.6%
 
2252361.6%
 
2322341.5%
 
2212311.5%
 
2352281.5%
 
2362251.5%
 
2222231.5%
 
2272221.5%
 
2342221.5%
 
2382201.5%
 
2392181.4%
 
2422131.4%
 
2202121.4%
 
2372071.4%
 
2412011.3%
 
2182011.3%
 
2452011.3%
 
Other values (151)931861.6%
 
ValueCountFrequency (%) 
01< 0.1%
 
581< 0.1%
 
592< 0.1%
 
651< 0.1%
 
731< 0.1%
 
781< 0.1%
 
802< 0.1%
 
811< 0.1%
 
833< 0.1%
 
852< 0.1%
 
ValueCountFrequency (%) 
2541901.3%
 
2532001.3%
 
2521891.2%
 
2511741.2%
 
2501921.3%
 
2491951.3%
 
2481781.2%
 
2471881.2%
 
2461811.2%
 
2452011.3%
 

Hillshade_Noon
Real number (ℝ≥0)

Distinct141
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218.9656085
Minimum99
Maximum254
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2020-12-22T11:52:03.811127image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum99
5-th percentile175
Q1207
median223
Q3235
95-th percentile250
Maximum254
Range155
Interquartile range (IQR)28

Descriptive statistics

Standard deviation22.80196554
Coefficient of variation (CV)0.1041349174
Kurtosis1.153484179
Mean218.9656085
Median Absolute Deviation (MAD)14
Skewness-0.9532317075
Sum3310760
Variance519.9296327
MonotocityNot monotonic
2020-12-22T11:52:04.015117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2253272.2%
 
2293242.1%
 
2263202.1%
 
2243132.1%
 
2303112.1%
 
2233032.0%
 
2322982.0%
 
2222972.0%
 
2282941.9%
 
2182931.9%
 
2212921.9%
 
2272891.9%
 
2312841.9%
 
2202721.8%
 
2362701.8%
 
2342691.8%
 
2162661.8%
 
2142631.7%
 
2332611.7%
 
2152551.7%
 
2112511.7%
 
2192471.6%
 
2172471.6%
 
2352321.5%
 
2442281.5%
 
Other values (116)811453.7%
 
ValueCountFrequency (%) 
994< 0.1%
 
1021< 0.1%
 
1031< 0.1%
 
1071< 0.1%
 
1112< 0.1%
 
1133< 0.1%
 
1141< 0.1%
 
1151< 0.1%
 
1161< 0.1%
 
1181< 0.1%
 
ValueCountFrequency (%) 
2541330.9%
 
2531631.1%
 
2521521.0%
 
2511831.2%
 
2501671.1%
 
2491761.2%
 
2481961.3%
 
2472101.4%
 
2462141.4%
 
2452071.4%
 

Hillshade_3pm
Real number (ℝ≥0)

Distinct247
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.0919974
Minimum0
Maximum248
Zeros88
Zeros (%)0.6%
Memory size118.2 KiB
2020-12-22T11:52:04.206116image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53
Q1106
median138
Q3167
95-th percentile207
Maximum248
Range248
Interquartile range (IQR)61

Descriptive statistics

Standard deviation45.89518871
Coefficient of variation (CV)0.3397328458
Kurtosis-0.08734390755
Mean135.0919974
Median Absolute Deviation (MAD)30
Skewness-0.3408272326
Sum2042591
Variance2106.368347
MonotocityNot monotonic
2020-12-22T11:52:04.390146image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1431821.2%
 
1491611.1%
 
1321561.0%
 
1331541.0%
 
1421541.0%
 
1361541.0%
 
1371521.0%
 
1381481.0%
 
1541481.0%
 
1521451.0%
 
1501441.0%
 
1571410.9%
 
1511390.9%
 
1351380.9%
 
1481380.9%
 
1441370.9%
 
1151360.9%
 
1561360.9%
 
1631350.9%
 
1241340.9%
 
1301330.9%
 
1181330.9%
 
1311320.9%
 
1291320.9%
 
1211300.9%
 
Other values (222)1152876.2%
 
ValueCountFrequency (%) 
0880.6%
 
11< 0.1%
 
33< 0.1%
 
41< 0.1%
 
62< 0.1%
 
71< 0.1%
 
81< 0.1%
 
92< 0.1%
 
103< 0.1%
 
112< 0.1%
 
ValueCountFrequency (%) 
2482< 0.1%
 
2474< 0.1%
 
2464< 0.1%
 
2454< 0.1%
 
2443< 0.1%
 
2434< 0.1%
 
2423< 0.1%
 
2413< 0.1%
 
2407< 0.1%
 
2395< 0.1%
 
Distinct2710
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1511.147288
Minimum0
Maximum6993
Zeros2
Zeros (%)< 0.1%
Memory size118.2 KiB
2020-12-22T11:52:04.575275image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile296.9
Q1730
median1256
Q31988.25
95-th percentile3663.05
Maximum6993
Range6993
Interquartile range (IQR)1258.25

Descriptive statistics

Standard deviation1099.936493
Coefficient of variation (CV)0.7278817235
Kurtosis3.385415788
Mean1511.147288
Median Absolute Deviation (MAD)595
Skewness1.617098874
Sum22848547
Variance1209860.288
MonotocityNot monotonic
2020-12-22T11:52:04.746295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
618650.4%
 
541510.3%
 
636450.3%
 
607430.3%
 
573420.3%
 
960420.3%
 
752410.3%
 
942400.3%
 
342400.3%
 
242400.3%
 
277390.3%
 
977390.3%
 
212380.3%
 
524370.2%
 
700370.2%
 
335370.2%
 
902370.2%
 
726360.2%
 
484360.2%
 
408360.2%
 
997350.2%
 
391350.2%
 
808350.2%
 
671340.2%
 
912340.2%
 
Other values (2685)1412693.4%
 
ValueCountFrequency (%) 
02< 0.1%
 
3090.1%
 
42110.1%
 
60100.1%
 
67200.1%
 
8580.1%
 
9090.1%
 
95190.1%
 
108250.2%
 
12080.1%
 
ValueCountFrequency (%) 
69931< 0.1%
 
68531< 0.1%
 
67231< 0.1%
 
66861< 0.1%
 
66611< 0.1%
 
66321< 0.1%
 
66151< 0.1%
 
66061< 0.1%
 
66001< 0.1%
 
65971< 0.1%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
11523 
1
3597 
ValueCountFrequency (%) 
01152376.2%
 
1359723.8%
 
2020-12-22T11:52:04.880301image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14621 
1
 
499
ValueCountFrequency (%) 
01462196.7%
 
14993.3%
 
2020-12-22T11:52:04.942268image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
8771 
1
6349 
ValueCountFrequency (%) 
0877158.0%
 
1634942.0%
 
2020-12-22T11:52:05.007304image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
10445 
1
4675 
ValueCountFrequency (%) 
01044569.1%
 
1467530.9%
 
2020-12-22T11:52:05.075295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type1
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14765 
1
 
355
ValueCountFrequency (%) 
01476597.7%
 
13552.3%
 
2020-12-22T11:52:05.138295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type2
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14497 
1
 
623
ValueCountFrequency (%) 
01449795.9%
 
16234.1%
 
2020-12-22T11:52:05.201271image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type3
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14158 
1
 
962
ValueCountFrequency (%) 
01415893.6%
 
19626.4%
 
2020-12-22T11:52:05.264334image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type4
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14277 
1
 
843
ValueCountFrequency (%) 
01427794.4%
 
18435.6%
 
2020-12-22T11:52:05.326295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type5
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14955 
1
 
165
ValueCountFrequency (%) 
01495598.9%
 
11651.1%
 
2020-12-22T11:52:05.393296image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type6
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14470 
1
 
650
ValueCountFrequency (%) 
01447095.7%
 
16504.3%
 
2020-12-22T11:52:05.458272image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type7
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15120 
ValueCountFrequency (%) 
015120100.0%
 
2020-12-22T11:52:05.521269image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type8
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15119 
1
 
1
ValueCountFrequency (%) 
015119> 99.9%
 
11< 0.1%
 
2020-12-22T11:52:05.564309image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type9
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15110 
1
 
10
ValueCountFrequency (%) 
01511099.9%
 
1100.1%
 
2020-12-22T11:52:05.627295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
12978 
1
2142 
ValueCountFrequency (%) 
01297885.8%
 
1214214.2%
 
2020-12-22T11:52:05.690269image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14714 
1
 
406
ValueCountFrequency (%) 
01471497.3%
 
14062.7%
 
2020-12-22T11:52:06.069713image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14893 
1
 
227
ValueCountFrequency (%) 
01489398.5%
 
12271.5%
 
2020-12-22T11:52:06.134295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14644 
1
 
476
ValueCountFrequency (%) 
01464496.9%
 
14763.1%
 
2020-12-22T11:52:06.201269image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14951 
1
 
169
ValueCountFrequency (%) 
01495198.9%
 
11691.1%
 
2020-12-22T11:52:06.270266image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type15
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15120 
ValueCountFrequency (%) 
015120100.0%
 
2020-12-22T11:52:06.329268image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15006 
1
 
114
ValueCountFrequency (%) 
01500699.2%
 
11140.8%
 
2020-12-22T11:52:06.376620image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14508 
1
 
612
ValueCountFrequency (%) 
01450896.0%
 
16124.0%
 
2020-12-22T11:52:06.439270image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15060 
1
 
60
ValueCountFrequency (%) 
01506099.6%
 
1600.4%
 
2020-12-22T11:52:06.501738image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15074 
1
 
46
ValueCountFrequency (%) 
01507499.7%
 
1460.3%
 
2020-12-22T11:52:06.562301image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14981 
1
 
139
ValueCountFrequency (%) 
01498199.1%
 
11390.9%
 
2020-12-22T11:52:06.627292image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15104 
1
 
16
ValueCountFrequency (%) 
01510499.9%
 
1160.1%
 
2020-12-22T11:52:06.698171image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14775 
1
 
345
ValueCountFrequency (%) 
01477597.7%
 
13452.3%
 
2020-12-22T11:52:06.761221image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14363 
1
 
757
ValueCountFrequency (%) 
01436395.0%
 
17575.0%
 
2020-12-22T11:52:06.825155image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14863 
1
 
257
ValueCountFrequency (%) 
01486398.3%
 
12571.7%
 
2020-12-22T11:52:06.888210image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15119 
1
 
1
ValueCountFrequency (%) 
015119> 99.9%
 
11< 0.1%
 
2020-12-22T11:52:06.950625image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15066 
1
 
54
ValueCountFrequency (%) 
01506699.6%
 
1540.4%
 
2020-12-22T11:52:07.022920image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15105 
1
 
15
ValueCountFrequency (%) 
01510599.9%
 
1150.1%
 
2020-12-22T11:52:07.086591image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15111 
1
 
9
ValueCountFrequency (%) 
01511199.9%
 
190.1%
 
2020-12-22T11:52:07.149593image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
13829 
1
 
1291
ValueCountFrequency (%) 
01382991.5%
 
112918.5%
 
2020-12-22T11:52:07.213631image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14395 
1
 
725
ValueCountFrequency (%) 
01439595.2%
 
17254.8%
 
2020-12-22T11:52:07.276590image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14788 
1
 
332
ValueCountFrequency (%) 
01478897.8%
 
13322.2%
 
2020-12-22T11:52:07.340662image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14430 
1
 
690
ValueCountFrequency (%) 
01443095.4%
 
16904.6%
 
2020-12-22T11:52:07.402623image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14504 
1
 
616
ValueCountFrequency (%) 
01450495.9%
 
16164.1%
 
2020-12-22T11:52:07.464629image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15098 
1
 
22
ValueCountFrequency (%) 
01509899.9%
 
1220.1%
 
2020-12-22T11:52:07.527591image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15018 
1
 
102
ValueCountFrequency (%) 
01501899.3%
 
11020.7%
 
2020-12-22T11:52:07.589592image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15110 
1
 
10
ValueCountFrequency (%) 
01511099.9%
 
1100.1%
 
2020-12-22T11:52:07.651591image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15086 
1
 
34
ValueCountFrequency (%) 
01508699.8%
 
1340.2%
 
2020-12-22T11:52:07.716626image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14392 
1
 
728
ValueCountFrequency (%) 
01439295.2%
 
17284.8%
 
2020-12-22T11:52:07.778624image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14463 
1
 
657
ValueCountFrequency (%) 
01446395.7%
 
16574.3%
 
2020-12-22T11:52:07.843617image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14661 
1
 
459
ValueCountFrequency (%) 
01466197.0%
 
14593.0%
 
2020-12-22T11:52:07.905624image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cover_Type
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2020-12-22T11:52:07.994023image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.000066141
Coefficient of variation (CV)0.5000165352
Kurtosis-1.250016528
Mean4
Median Absolute Deviation (MAD)2
Skewness0
Sum60480
Variance4.000264568
MonotocityNot monotonic
2020-12-22T11:52:08.100005image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
7216014.3%
 
6216014.3%
 
5216014.3%
 
4216014.3%
 
3216014.3%
 
2216014.3%
 
1216014.3%
 
ValueCountFrequency (%) 
1216014.3%
 
2216014.3%
 
3216014.3%
 
4216014.3%
 
5216014.3%
 
6216014.3%
 
7216014.3%
 
ValueCountFrequency (%) 
7216014.3%
 
6216014.3%
 
5216014.3%
 
4216014.3%
 
3216014.3%
 
2216014.3%
 
1216014.3%
 

Interactions

2020-12-22T11:51:23.220845image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:23.407947image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:23.596977image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:23.771090image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:23.937127image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:24.117011image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:24.294282image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:24.473354image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:24.639317image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:24.830211image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:24.997070image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:25.184895image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:25.354433image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:25.534456image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:25.711429image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:25.889430image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:26.059468image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:26.248431image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:26.430461image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:26.615708image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:26.782082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:26.969985image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:27.139013image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:27.326989image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:27.495984image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:27.669988image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:27.848600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:28.028601image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:28.191606image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:28.389597image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:28.563597image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:28.749600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:29.070387image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:29.258028image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:29.429603image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:29.610733image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:29.778598image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:29.945600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:30.112628image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:30.292082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:30.454111image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:30.631115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:30.787416image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:30.960082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:31.119083image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:31.309081image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:31.487108image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:31.669084image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:31.831109image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:32.024085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:32.206210image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:32.392455image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:32.572263image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:32.767016image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:32.993007image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:33.190082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:33.376199image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:33.562044image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:33.744004image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:33.941031image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:34.190005image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:34.423004image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:34.669251image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:34.907633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:35.133926image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:35.357004image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:35.532585image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:35.716075image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:35.925100image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:36.122107image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:36.285007image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:36.474006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:36.652018image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:36.836038image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:37.034005image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:37.222046image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:37.388006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:37.576031image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:37.752030image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:37.947006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:38.131006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:38.538006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:38.715004image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:38.906029image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:39.088004image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:39.247213image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:39.413648image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:39.583532image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:39.752911image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:39.923565image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:40.099568image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:40.275531image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:40.438425image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:40.617531image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:40.775533image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:40.952533image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:41.110558image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:41.332405image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:41.562615image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:41.812651image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:42.004637image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:42.241732image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:42.458127image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:42.665351image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:42.845382image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:43.077350image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:43.292441image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:43.528929image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:43.722413image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:43.930675image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:44.124285image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:44.344379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:44.535354image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:44.719556image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:44.929542image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:45.123657image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:45.321536image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:45.540601image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:45.725540image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:45.900537image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:46.096642image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:46.326556image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:46.513563image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:46.704536image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:46.891536image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:47.097569image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:47.286569image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:47.482798image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:47.662730image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:47.862539image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:48.050389image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:48.237539image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:48.415540image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:48.595571image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:48.758562image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:48.917568image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:49.066538image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:49.243846image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:49.435327image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:49.636118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:49.800639image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:50.249382image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:50.455266image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:50.653662image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-22T11:52:08.348559image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-22T11:52:11.409413image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-22T11:52:14.484148image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-22T11:52:17.356552image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-12-22T11:51:51.205634image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-22T11:51:58.573432image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

IdElevationAspectSlopeHorizontal_Distance_To_HydrologyVertical_Distance_To_HydrologyHorizontal_Distance_To_RoadwaysHillshade_9amHillshade_NoonHillshade_3pmHorizontal_Distance_To_Fire_PointsWilderness_Area1Wilderness_Area2Wilderness_Area3Wilderness_Area4Soil_Type1Soil_Type2Soil_Type3Soil_Type4Soil_Type5Soil_Type6Soil_Type7Soil_Type8Soil_Type9Soil_Type10Soil_Type11Soil_Type12Soil_Type13Soil_Type14Soil_Type15Soil_Type16Soil_Type17Soil_Type18Soil_Type19Soil_Type20Soil_Type21Soil_Type22Soil_Type23Soil_Type24Soil_Type25Soil_Type26Soil_Type27Soil_Type28Soil_Type29Soil_Type30Soil_Type31Soil_Type32Soil_Type33Soil_Type34Soil_Type35Soil_Type36Soil_Type37Soil_Type38Soil_Type39Soil_Type40Cover_Type
01259651325805102212321486279100000000000000000000000000000001000000000005
122590562212-63902202351516225100000000000000000000000000000001000000000005
23280413992686531802342381356121100000000000000100000000000000000000000000002
3427851551824211830902382381226211100000000000000000000000000000000100000000002
452595452153-13912202341506172100000000000000000000000000000001000000000005
5625791326300-15672302371406031100000000000000000000000000000001000000000002
67260645727056332222251386256100000000000000000000000000000001000000000005
78260549423475732222301446228100000000000000000000000000000001000000000005
892617459240566662232211336244100000000000000000000000000000001000000000005
91026125910247116362282191246230100000000000000000000000000000001000000000005

Last rows

IdElevationAspectSlopeHorizontal_Distance_To_HydrologyVertical_Distance_To_HydrologyHorizontal_Distance_To_RoadwaysHillshade_9amHillshade_NoonHillshade_3pmHorizontal_Distance_To_Fire_PointsWilderness_Area1Wilderness_Area2Wilderness_Area3Wilderness_Area4Soil_Type1Soil_Type2Soil_Type3Soil_Type4Soil_Type5Soil_Type6Soil_Type7Soil_Type8Soil_Type9Soil_Type10Soil_Type11Soil_Type12Soil_Type13Soil_Type14Soil_Type15Soil_Type16Soil_Type17Soil_Type18Soil_Type19Soil_Type20Soil_Type21Soil_Type22Soil_Type23Soil_Type24Soil_Type25Soil_Type26Soil_Type27Soil_Type28Soil_Type29Soil_Type30Soil_Type31Soil_Type32Soil_Type33Soil_Type34Soil_Type35Soil_Type36Soil_Type37Soil_Type38Soil_Type39Soil_Type40Cover_Type
151101511125083326671644204173911385001000000000010000000000000000000000000000006
1511115112261059176010674231202981328001000000000010000000000000000000000000000006
1511215113260038251240589212178891261001000000000010000000000000000000000000000006
151131511426881041544310805245219991266001000000000001000000000000000000000000000003
1511415115267010812624247302412251121231001000000000001000000000000000000000000000003
151151511626072432325876601702512141282001000010000000000000000000000000000000000003
1511615117260312119633195618249221911325001000010000000000000000000000000000000000003
1511715118249213425365117335250220831187001000010000000000000000000000000000000000003
1511815119248716728218101242229237119932001000010000000000000000000000000000000000003
151191512024751973431978270189244164914001001000000000000000000000000000000000000003